bbemkr: Bayesian bandwidth estimation for multivariate kernel regression with Gaussian error

Bayesian bandwidth estimation for Nadaraya-Watson type multivariate kernel regression with Gaussian error density

Install the latest version of this package by entering the following in R:
install.packages("bbemkr")
AuthorHan Lin Shang and Xibin Zhang
Date of publication2014-04-05 08:11:58
MaintainerHan Lin Shang <hanlin.shang@anu.edu.au>
LicenseGPL (>= 2)
Version2.0
https://sites.google.com/site/hanlinshangswebsite/

View on CRAN

Man pages

bbemkr-package: Bayesian bandwidth estimation for multivariate kernel...

cost: Negative of log posterior associated with the bandwidths

cost2_gaussian: Negative of log posterior associated with the error variance

cost_admkr: Negative of log posterior associated with the bandwidths

cov_chol: Calculate log marginal likeliood from MCMC output

cov_chol_admkr: Calculate log marginal likelihood from MCMC output

data_x: Simulated three-dimensional regressors

data_ynorm: Simulated response variable

data_yt: Simulated response variable

gibbs_admkr_erro: Estimating bandwidth of the kernel-form error density

gibbs_admkr_nw: Estimating bandwidths of the regressors

ker: Type of kernel function

kern: Calculate the R square value and mean square error as...

LaplaceMetropolis_admkr: Laplace-Metropolis estimator of log marginal likelihood

LaplaceMetropolis_gaussian: Laplace-Metropolis estimator of log marginal likelihood

logdensity_admkr: Calculate an estimate of log posterior ordinate used in the...

logdensity_gaussian: Calculate an estimate of log posterior ordinate used in the...

loglikelihood_admkr: Calculate the log likelihood used in the Chib's (1995) log...

loglikelihood_gaussian: Calculate the log likelihood used in the Chib's (1995) log...

logpriorh2: Prior of square bandwidths

logpriors_admkr: Calculate the log prior used in the log marginal density of...

logpriors_gaussian: Calculate the log prior used in the log marginal density of...

mcmcrecord_admkr: MCMC iterations

mcmcrecord_gaussian: MCMC iterations

NadarayaWatsonkernel: Nadaraya-Watson kernel estimator

np_gibbs: Estimating bandwidths of the regressors

nrr: Normal reference rule for estimating bandwidths

warmup_admkr: Burn-in period

warmup_gaussian: Burn-in period

xm: Values of true regression function

Functions

bbemkr Man page
bbemkr-package Man page
cost2_gaussian Man page
cost_admkr Man page
cost_gaussian Man page
cov_chol Man page
cov_chol_admkr Man page
data_x Man page
data_ynorm Man page
data_yt Man page
gibbs_admkr_erro Man page
gibbs_admkr_nw Man page
ker Man page
kern Man page
LaplaceMetropolis_admkr Man page
LaplaceMetropolis_gaussian Man page
logdensity_admkr Man page
logdensity_gaussian Man page
loglikelihood_admkr Man page
loglikelihood_gaussian Man page
logpriorh2 Man page
logpriors_admkr Man page
logpriors_gaussian Man page
mcmcrecord_admkr Man page
mcmcrecord_gaussian Man page
NadarayaWatsonkernel Man page
np_gibbs Man page
nrr Man page
warmup_admkr Man page
warmup_gaussian Man page
xm Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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